196 research outputs found
Population Structure of Mountain Plover as Determined Us ing Nuclear Microsatellites
Moountainuntai Plloverove (Charadrius montanus) is a specie s of conservation concern that has experienced significant habitat loss an d population decline. This, couple d with previous observation s that the species exhibits strong fidelity to breeding grounds, suggests that breeding population s may be genetically differentiate d an d possibly suffer from reduced genetic variation associate d with relatively small population sizes. A previous genetic study comparing mitochondrial DNA sequences of plover s in Montana and Colorado found high level s of genetic variability and very little genetic differentiation among breeding locale s. Because mitochondrial DNA can track only female movement s an d is sample d from only one locus, we used 14 nu clear micro satellite lo ci to further examine population structure, there by bot h documenting male movement s and providing a more comprehensive vie w of genetic structure. We found no significant differences among breeding population s. The most likely number of unique genetic clusters was one, suggesting that all sampled breeding locations comprise a single relatively homogenous gene pool. Level s of genetic diversity was similar across all four population s, with the greatest diver sit y in the southern plains population. We speculate that the lack of detectable genetic differentiation among population s is due to sufficient gene flow among breeding population s that might en sue if at least some pair bon ds are formed when birds form mixed flocks on wintering grounds. This study corroborate s and expands upon the findings of a previous mitochondrial DNA study providing a more comprehensive vie w of Mountain Plover population structure
An experimental comparison of composite and grab sampling of stream water for metagenetic analysis of environmental DNA
Use of environmental DNA (eDNA) to assess distributions of aquatic and semi-aquatic macroorganisms is promising, but sampling schemes may need to be tailored to specific objectives. Given the potentially high variance in aquatic eDNA among replicate grab samples, compositing smaller water volumes collected over a period of time may be more effective for some applications. In this study, we compared eDNA profiles from composite water samples aggregated over three hours with grab water samples. Both sampling patterns were performed with identical autosamplers paired at two different sites in a headwater stream environment, augmented with exogenous fish eDNA from an upstream rearing facility. Samples were filtered through 0.8 ÎĽm cellulose nitrate filters and DNA was extracted with a cetyl trimethylammonium bromide procedure. Eukaryotic and bacterial community profiles were derived by amplicon sequencing of 12S ribosomal, 16S ribosomal, and cytochrome oxidase I loci. Operational taxa were assigned to genus with a lowest common ancestor approach for eukaryotes and to family with the RDP Classifier software for prokaryotes. Eukaryotic community profiles were more consistent with composite sampling than grab sampling. Downstream, rarefaction curves suggested faster taxon accumulation for composite samples, and estimated richness was higher for composite samples as a set than for grab samples. Upstream, composite sampling produced lower estimated richness than grab samples, but with overlapping standard errors. Furthermore, a bimodal pattern of richness as a function of sequence counts suggested the impact of clumped particles on upstream samples. Bacterial profiles were insensitive to sample method, consistent with the more even dispersion expected for bacteria compared with eukaryotic eDNA. Overall, samples composited over 3 h performed equal to or better than triplicate grab sampling for quantitative community metrics, despite the higher total sequencing effort provided to grab replicates. On the other hand, taxon-specific detection rates did not differ appreciably and the two methods gave similar estimates of the ratio of the common fish genera Salmo and Coregonus at each site. Unexpectedly, Salmo eDNA dropped out substantially faster than Coregonus eDNA between the two sites regardless of sampling method, suggesting that differential settling affects the estimation of relative abundance. We identified bacterial patterns that were associated with eukaryotic diversity, suggesting potential roles as biomarkers of sample representativeness
Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer
Interbasin water transfers are becoming an increasingly common tool to satisfy municipal and agricultural water demand, but their impacts on movement and gene flow of aquatic organisms are poorly understood. The Grand Ditch is an interbasin water transfer that diverts water from tributaries of the upper Colorado River on the west side of the Continental Divide to the upper Cache la Poudre River on the east side of the Continental Divide. We used single nucleotide polymorphisms to characterize population genetic structure in cutthroat trout (Oncorhynchus clarkii) and determine if fish utilize the Grand Ditch as a movement corridor. Samples were collected from two sites on the west side and three sites on the east side of the Continental Divide. We identified two or three genetic clusters, and relative migration rates and spatial distributions of admixed individuals indicated that the Grand Ditch facilitated bidirectional fish movement across the Continental Divide, a major biogeographic barrier. Previous studies have demonstrated ecological impacts of interbasin water transfers, but our study is one of the first to use genetics to understand how interbasin water transfers affect connectivity between previously isolated watersheds. We also discuss implications on native trout management and balancing water demand and biodiversity conservation
Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations
Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R-2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.Endangered Species Recovery Fund (WWF, Environment Canada, Ontario Ministry of Natural Resources)US Bureau of Land ManagementUS Geological SurveyWyoming Game and Fish Departmen
Rapid Microsatellite Identification from Illumina Paired-End Genomic Sequencing in Two Birds and a Snake
Identification of microsatellites, or simple sequence repeats (SSRs), can be a time-consuming and costly investment requiring enrichment, cloning, and sequencing of candidate loci. Recently, however, high throughput sequencing (with or without prior enrichment for specific SSR loci) has been utilized to identify SSR loci. The direct “Seq-to-SSR” approach has an advantage over enrichment-based strategies in that it does not require a priori selection of particular motifs, or prior knowledge of genomic SSR content. It has been more expensive per SSR locus recovered, however, particularly for genomes with few SSR loci, such as bird genomes. The longer but relatively more expensive 454 reads have been preferred over less expensive Illumina reads. Here, we use Illumina paired-end sequence data to identify potentially amplifiable SSR loci (PALs) from a snake (the Burmese python, Python molurus bivittatus), and directly compare these results to those from 454 data. We also compare the python results to results from Illumina sequencing of two bird genomes (Gunnison Sage-grouse, Centrocercus minimus, and Clark's Nutcracker, Nucifraga columbiana), which have considerably fewer SSRs than the python. We show that direct Illumina Seq-to-SSR can identify and characterize thousands of potentially amplifiable SSR loci for as little as $10 per sample – a fraction of the cost of 454 sequencing. Given that Illumina Seq-to-SSR is effective, inexpensive, and reliable even for species such as birds that have few SSR loci, it seems that there are now few situations for which prior hybridization is justifiable
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Regional variation in mtDNA of the lesser prairie-chicken
Cumulative loss of habitat and long-term decline in the populations of the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) have led to concerns for the species’ viability throughout its range in the southern Great Plains. For more efficient conservation past and present distributions of genetic variation need to be understood. We examined the distribution of mitochondrial DNA (mtDNA) variation in the Lesser Prairie-Chicken across Kansas, Colorado, Oklahoma, and New Mexico. Throughout the range we found little genetic differentiation except for the population in New Mexico, which was significantly different from most other populations. We did, however, find significant isolation by distance at the rangewide scale (r = 0.698). We found no relationship between haplotype phylogeny and geography, and our analyses provide evidence for a post-glacial population expansion within the species that is consistent with the idea that speciation within Tympanuchus is recent. Conservation actions that increase the likelihood of genetically viable populations in the future should be evaluated for implementation.This is the publisher’s final pdf. The article is copyrighted by Cooper Ornithological Society and published by Central Ornithology Publication Office. It can be found at: http://www.aoucospubs.org/loi/condKeywords: prairie grouse, Tympanuchus pallidicinctus, genetic diversity, Lesser Prairie-Chicken, DNA, mitochondrial DNAKeywords: prairie grouse, Tympanuchus pallidicinctus, genetic diversity, Lesser Prairie-Chicken, DNA, mitochondrial DN
Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach
Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.U.S. Bureau of Land ManagementU.S. Geological SurveyWyoming Game and Fish Departmen
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Rangewide genetic analysis of Lesser Prairie-Chicken reveals population structure, range expansion, and possible introgression
The distribution of the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) has been markedly reduced due to loss and fragmentation of habitat. Portions of the historical range, however, have been recolonized and even expanded due to planting of conservation reserve program (CRP) fields that provide favorable vegetation structure for Lesser Prairie-Chickens. The source population(s) feeding the range expansion is unknown, yet has resulted in overlap between Lesser and Greater Prairie-Chickens (T. cupido) increasing the potential for hybridization. Our objectives were to characterize connectivity and genetic diversity among populations, identify source population(s) of recent range expansion, and examine hybridization with the Greater Prairie-Chicken. We analyzed 640 samples from across the range using 13 microsatellites. We identified three to four populations corresponding largely to ecoregions. The Shinnery Oak Prairie and Sand Sagebrush Prairie represented genetically distinct populations (F (ST) > 0.034 and F (ST) > 0.023 respectively). The Shortgrass/CRP Mosaic and Mixed Grass ecoregions appeared admixed (F (ST) = 0.009). Genetic diversity was similar among ecoregions and N (e) ranged from 142 (95 % CI 99-236) for the Shortgrass/CRP Mosaic to 296 (95 % CI 233-396) in the Mixed Grass Prairie. No recent migration was detected among ecoregions, except asymmetric dispersal from both the Mixed Grass Prairie and to a lesser extent the Sand Sagebrush Prairie north into adjacent Shortgrass/CRP Mosaic (m = 0.207, 95 % CI 0.116-0.298, m = 0.097, 95 % CI 0.010-0.183, respectively). Indices investigating potential hybridization in the Shortgrass/CRP Mosaic revealed that six of the 13 individuals with hybrid phenotypes were significantly admixed suggesting hybridization. Continued monitoring of diversity within and among ecoregions is warranted as are actions promoting genetic connectivity and range expansion.Keywords: Spatial genetic population structure, Genetic diversity, Tympanuchus pallidicinctus, Gene flow, Hybridizatio
Next-generation conservation genetics and biodiversity monitoring
This special issue of Evolutionary Applications consists of 10 publications investigating
the use of next-generation
tools and techniques in population genetic analyses and
biodiversity assessment. The special issue stems from a 2016 Next Generation
Genetic Monitoring Workshop, hosted by the National Institute for Mathematical
and Biological Synthesis (NIMBioS) in Tennessee, USA. The improved accessibility of
next-generation
sequencing platforms has allowed molecular ecologists to rapidly
produce large amounts of data. However, with the increased availability of new
genomic markers and mathematical techniques, care is needed in selecting appropriate
study designs, interpreting results in light of conservation concerns, and determining
appropriate management actions. This special issue identifies key attributes
of successful genetic data analyses in biodiversity evaluation and suggests ways to
improve analyses and their application in current population and conservation genetics
research
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